RandomProjection

java.lang.Object
- weka.filters.Filter
- - weka.filters.unsupervised.attribute.RandomProjection

All Implemented Interfaces:: java.io.Serializable, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler, UnsupervisedFilter

public class RandomProjection
extends Filter
implements UnsupervisedFilter, OptionHandler, TechnicalInformationHandler

Reduces the dimensionality of the data by projecting it onto a lower dimensional subspace using a random matrix with columns of unit length (i.e. It will reduce the number of attributes in the data while preserving much of its variation like PCA, but at a much less computational cost).
It first applies the NominalToBinary filter to convert all attributes to numeric before reducing the dimension. It preserves the class attribute.

For more information, see:

Dmitriy Fradkin, David Madigan: Experiments with random projections for machine learning. In: KDD '03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, New York, NY, USA, 517-522, 003.

BibTeX:

 @inproceedings{Fradkin003,
    address = {New York, NY, USA},
    author = {Dmitriy Fradkin and David Madigan},
    booktitle = {KDD '03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining},
    pages = {517-522},
    publisher = {ACM Press},
    title = {Experiments with random projections for machine learning},
    year = {003}
 }

Valid options are:

 -N <number>
  The number of dimensions (attributes) the data should be reduced to
  (default 10; exclusive of the class attribute, if it is set).

 -D [SPARSE1|SPARSE2|GAUSSIAN]
  The distribution to use for calculating the random matrix.
  Sparse1 is:
    sqrt(3)*{-1 with prob(1/6), 0 with prob(2/3), +1 with prob(1/6)}
  Sparse2 is:
    {-1 with prob(1/2), +1 with prob(1/2)}

 -P <percent>
  The percentage of dimensions (attributes) the data should
  be reduced to (exclusive of the class attribute, if it is set). This -N
  option is ignored if this option is present and is greater
  than zero.

 -M
  Replace missing values using the ReplaceMissingValues filter

 -R <num>
  The random seed for the random number generator used for
  calculating the random matrix (default 42).

Version:: $Revision: 10832 $ [1.0 - 22 July 2003 - Initial version (Ashraf M. Kibriya)]
Author:: Ashraf M. Kibriya (amk14@cs.waikato.ac.nz)
See Also:: Serialized Form

Field Summary

Fields
Modifier and Type	Field and Description
`static int`	`GAUSSIAN` distribution type: gaussian
`static int`	`SPARSE1` distribution type: sparse 1
`static int`	`SPARSE2` distribution type: sparse 2
`static Tag[]`	`TAGS_DSTRS_TYPE` The types of distributions that can be used for calculating the random matrix

Constructor Summary

Constructors
Constructor and Description

RandomProjection()

Constructors
Constructor and Description
`RandomProjection()`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`boolean`	`batchFinished()` Signify that this batch of input to the filter is finished.
`java.lang.String`	`distributionTipText()` Returns the tip text for this property
`Capabilities`	`getCapabilities()` Returns the Capabilities of this filter.
`SelectedTag`	`getDistribution()` Returns the current distribution that'll be used for calculating the random matrix
`int`	`getNumberOfAttributes()` Gets the current number of attributes (dimensionality) to which the data will be reduced to.
`java.lang.String[]`	`getOptions()` Gets the current settings of the filter.
`double`	`getPercent()` Gets the percent the attributes (dimensions) of the data will be reduced to
`long`	`getRandomSeed()` Gets the random seed of the random number generator
`boolean`	`getReplaceMissingValues()` Gets the current setting for using ReplaceMissingValues filter
`java.lang.String`	`getRevision()` Returns the revision string.
`TechnicalInformation`	`getTechnicalInformation()` Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
`java.lang.String`	`globalInfo()` Returns a string describing this filter
`boolean`	`input(Instance instance)` Input an instance for filtering.
`java.util.Enumeration`	`listOptions()` Returns an enumeration describing the available options.
`static void`	`main(java.lang.String[] argv)` Main method for testing this class.
`java.lang.String`	`numberOfAttributesTipText()` Returns the tip text for this property
`java.lang.String`	`percentTipText()` Returns the tip text for this property
`java.lang.String`	`randomSeedTipText()` Returns the tip text for this property
`java.lang.String`	`replaceMissingValuesTipText()` Returns the tip text for this property
`void`	`setDistribution(SelectedTag newDstr)` Sets the distribution to use for calculating the random matrix
`boolean`	`setInputFormat(Instances instanceInfo)` Sets the format of the input instances.
`void`	`setNumberOfAttributes(int newAttNum)` Sets the number of attributes (dimensions) the data should be reduced to
`void`	`setOptions(java.lang.String[] options)` Parses a given list of options.
`void`	`setPercent(double newPercent)` Sets the percent the attributes (dimensions) of the data should be reduced to
`void`	`setRandomSeed(long seed)` Sets the random seed of the random number generator
`void`	`setReplaceMissingValues(boolean t)` Sets either to use replace missing values filter or not

Methods inherited from class weka.filters.Filter
batchFilterFile, filterFile, getCapabilities, getOutputFormat, isFirstBatchDone, isNewBatch, isOutputFormatDefined, makeCopies, makeCopy, numPendingOutput, output, outputPeek, toString, useFilter, wekaStaticWrapper

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Field Detail
  - SPARSE1
```
public static final int SPARSE1
```
    distribution type: sparse 1
    
    See Also:
    
    Constant Field Values
  - SPARSE2
```
public static final int SPARSE2
```
    distribution type: sparse 2
    
    See Also:
    
    Constant Field Values
  - GAUSSIAN
```
public static final int GAUSSIAN
```
    distribution type: gaussian
    
    See Also:
    
    Constant Field Values
  - TAGS_DSTRS_TYPE
```
public static final Tag[] TAGS_DSTRS_TYPE
```
    The types of distributions that can be used for calculating the random matrix
- Constructor Detail
  - RandomProjection
```
public RandomProjection()
```
- Method Detail
  - listOptions
```
public java.util.Enumeration listOptions()
```
    Returns an enumeration describing the available options.
    
    Specified by:
    
    listOptions in interface OptionHandler
    
    Returns:
    
    an enumeration of all the available options.
  - setOptions
```
public void setOptions(java.lang.String[] options)
                throws java.lang.Exception
```
    Parses a given list of options.
    Valid options are:
```
 -N <number>
  The number of dimensions (attributes) the data should be reduced to
  (default 10; exclusive of the class attribute, if it is set).
 
```
```
 -D [SPARSE1|SPARSE2|GAUSSIAN]
  The distribution to use for calculating the random matrix.
  Sparse1 is:
    sqrt(3)*{-1 with prob(1/6), 0 with prob(2/3), +1 with prob(1/6)}
  Sparse2 is:
    {-1 with prob(1/2), +1 with prob(1/2)}
 
```
```
 -P <percent>
  The percentage of dimensions (attributes) the data should
  be reduced to (exclusive of the class attribute, if it is set). This -N
  option is ignored if this option is present and is greater
  than zero.
 
```
```
 -M
  Replace missing values using the ReplaceMissingValues filter
 
```
```
 -R <num>
  The random seed for the random number generator used for
  calculating the random matrix (default 42).
 
```
    Specified by:
    
    setOptions in interface OptionHandler
    
    Parameters:
    
    options - the list of options as an array of strings
    
    Throws:
    
    java.lang.Exception - if an option is not supported
  - getOptions
```
public java.lang.String[] getOptions()
```
    Gets the current settings of the filter.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Returns:
    
    an array of strings suitable for passing to setOptions
  - globalInfo
```
public java.lang.String globalInfo()
```
    Returns a string describing this filter
    
    Returns:
    
    a description of the filter suitable for displaying in the explorer/experimenter gui
  - getTechnicalInformation
```
public TechnicalInformation getTechnicalInformation()
```
    Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
    
    Specified by:
    
    getTechnicalInformation in interface TechnicalInformationHandler
    
    Returns:
    
    the technical information about this class
  - numberOfAttributesTipText
```
public java.lang.String numberOfAttributesTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setNumberOfAttributes
```
public void setNumberOfAttributes(int newAttNum)
```
    Sets the number of attributes (dimensions) the data should be reduced to
    
    Parameters:
    
    newAttNum - the goal for the dimensions
  - getNumberOfAttributes
```
public int getNumberOfAttributes()
```
    Gets the current number of attributes (dimensionality) to which the data will be reduced to.
    
    Returns:
    
    the number of dimensions
  - percentTipText
```
public java.lang.String percentTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setPercent
```
public void setPercent(double newPercent)
```
    Sets the percent the attributes (dimensions) of the data should be reduced to
    
    Parameters:
    
    newPercent - the percentage of attributes
  - getPercent
```
public double getPercent()
```
    Gets the percent the attributes (dimensions) of the data will be reduced to
    
    Returns:
    
    the percentage of attributes
  - randomSeedTipText
```
public java.lang.String randomSeedTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setRandomSeed
```
public void setRandomSeed(long seed)
```
    Sets the random seed of the random number generator
    
    Parameters:
    
    seed - the random seed value
  - getRandomSeed
```
public long getRandomSeed()
```
    Gets the random seed of the random number generator
    
    Returns:
    
    the random seed value
  - distributionTipText
```
public java.lang.String distributionTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setDistribution
```
public void setDistribution(SelectedTag newDstr)
```
    Sets the distribution to use for calculating the random matrix
    
    Parameters:
    
    newDstr - the distribution to use
  - getDistribution
```
public SelectedTag getDistribution()
```
    Returns the current distribution that'll be used for calculating the random matrix
    
    Returns:
    
    the current distribution
  - replaceMissingValuesTipText
```
public java.lang.String replaceMissingValuesTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setReplaceMissingValues
```
public void setReplaceMissingValues(boolean t)
```
    Sets either to use replace missing values filter or not
    
    Parameters:
    
    t - if true then the replace missing values is used
  - getReplaceMissingValues
```
public boolean getReplaceMissingValues()
```
    Gets the current setting for using ReplaceMissingValues filter
    
    Returns:
    
    true if the replace missing values filter is used
  - getCapabilities
```
public Capabilities getCapabilities()
```
    Returns the Capabilities of this filter.
    
    Specified by:
    
    getCapabilities in interface CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class Filter
    
    Returns:
    
    the capabilities of this object
    
    See Also:
    
    Capabilities
  - setInputFormat
```
public boolean setInputFormat(Instances instanceInfo)
                       throws java.lang.Exception
```
    Sets the format of the input instances.
    
    Overrides:
    
    setInputFormat in class Filter
    
    Parameters:
    
    instanceInfo - an Instances object containing the input instance structure (any instances contained in the object are ignored - only the structure is required).
    
    Returns:
    
    true if the outputFormat may be collected immediately
    
    Throws:
    
    java.lang.Exception - if the input format can't be set successfully
  - input
```
public boolean input(Instance instance)
              throws java.lang.Exception
```
    Input an instance for filtering.
    
    Overrides:
    
    input in class Filter
    
    Parameters:
    
    instance - the input instance
    
    Returns:
    
    true if the filtered instance may now be collected with output().
    
    Throws:
    
    java.lang.IllegalStateException - if no input format has been set
    
    java.lang.NullPointerException - if the input format has not been defined.
    
    java.lang.Exception - if the input instance was not of the correct format or if there was a problem with the filtering.
  - batchFinished
```
public boolean batchFinished()
                      throws java.lang.Exception
```
    Signify that this batch of input to the filter is finished.
    
    Overrides:
    
    batchFinished in class Filter
    
    Returns:
    
    true if there are instances pending output
    
    Throws:
    
    java.lang.NullPointerException - if no input structure has been defined,
    
    java.lang.Exception - if there was a problem finishing the batch.
  - getRevision
```
public java.lang.String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class Filter
    
    Returns:
    
    the revision
  - main
```
public static void main(java.lang.String[] argv)
```
    Main method for testing this class.
    
    Parameters:
    
    argv - should contain arguments to the filter: use -h for help

Class RandomProjection

Field Summary

Constructor Summary

Method Summary

Methods inherited from class weka.filters.Filter

Methods inherited from class java.lang.Object

Field Detail

SPARSE1

SPARSE2

GAUSSIAN

TAGS_DSTRS_TYPE

Constructor Detail

RandomProjection

Method Detail

listOptions

setOptions

getOptions

globalInfo

getTechnicalInformation

numberOfAttributesTipText

setNumberOfAttributes

getNumberOfAttributes

percentTipText

setPercent

getPercent

randomSeedTipText

setRandomSeed

getRandomSeed

distributionTipText

setDistribution

getDistribution

replaceMissingValuesTipText

setReplaceMissingValues

getReplaceMissingValues

getCapabilities

setInputFormat

input

batchFinished

getRevision

main